scholarly journals Acceptance sampling plans for inverse Weibull distribution based on truncated life test

2017 ◽  
Vol 6 (3) ◽  
pp. 169-178 ◽  
Author(s):  
Sukhdev Singh ◽  
Yogesh Mani Tripathi
Keyword(s):  
Weibull Distribution ◽  
Acceptance Sampling ◽  
Life Test ◽  
Sampling Plans ◽  
Acceptance Sampling Plans ◽  
Inverse Weibull Distribution ◽  
Truncated Life Test

The transmuted generalized inverse Weibull distribution in acceptance sampling plans based on life tests

2018 ◽  
Vol 40 (16) ◽  
pp. 4432-4443 ◽  
Author(s):  
Amer Ibrahim Al-Omari
Keyword(s):  
Weibull Distribution ◽  
Generalized Inverse ◽  
Real Data ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Operating Characteristic Function ◽  
Acceptance Sampling Plans ◽  
Inverse Weibull Distribution ◽  
Product Lifetime ◽  
Truncated Life Test

In this paper, designing of acceptance sampling plans for the truncated life test is suggested by assuming that the product lifetime follows transmuted generalized inverse Weibull distribution (TGIWD). For various values of the TGIWD parameters, the minimum sample sizes required to ensure the specified mean life are obtained, as well as the operating characteristic function values and producer’s risk of the suggested sampling plan are calculated. The results are explained by numerical examples and an application of real data is considered for illustration.

scholarly journals Double Acceptance Sampling Plans Based on Truncated Life Tests for the Marshall-Olkin Extended Exponential Distribution

2016 ◽  
Vol 40 (3) ◽  
Author(s):  
G. Srinivasa Rao
Keyword(s):  
Exponential Distribution ◽  
Acceptance Sampling ◽  
Life Test ◽  
Producer’S Risk ◽  
Sampling Plans ◽  
Confidence Levels ◽  
Acceptance Sampling Plans ◽  
Truncated Life Test ◽  
Life Tests

In this paper, double acceptance sampling plans are developed for a truncated life test, when the lifetime of an item follows the Marshall-Olkin extended exponential distribution. The probability of acceptance is calculated for different consumer’s confidence levels fixing the producer’s risk at 0.05. The probability of acceptance and the producer’s risk are explained by means of examples.

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